期刊文献+

常州市燃气管网破坏的人工神经网络预测模型 被引量:4

Artificial Network Prediction Model for Gas Pipeline Network Failure in Changzhou City
下载PDF
导出
摘要 作为一种高效清洁的能源,燃气已经成为城市能源中的重要一员,燃气管网破坏亦成为城市所面临的重大安全隐患。城市埋地燃气管网的破坏风险,往往受到多种影响因素的共同作用。通过分析常州市埋地燃气管网破坏的影响因素,确定了地面沉降、地裂缝、城市内涝、土壤腐蚀等4个风险评价因子。运用MATLAB中的人工神经网络工具,通过人工神经网络计算,优化了模型网络结构,建立了常州市埋地燃气管网破坏风险预测的人工神经网络模型。分析计算结果,并为常州市埋地燃气管网的安全防护提供了建议。 As a kind of highly efficient and clean energy,gas has become an important part of urban energy,and the destruction of gas pipe network has also become a major problem facing cities.The risk of urban buried gas pipe network is often affected by many factors.Four risk assessment factors,such as ground subsidence and ground crack,are determined by analyzing the factors affecting the damage of buried gas pipe network in Changzhou.Using the artificial neural network tool in MATLAB,the model network structure is optimized through the artificial neural network calculation,and the artificial neural network model for the prediction of the damage risk of buried gas pipe network in Changzhou city is established.The results are analyzed and some suggestions are provided for the safety protection of buried gas pipe network in Changzhou city.
作者 朱庆杰 张建龙 陈艳华 赵炫皓 万永华 ZHU Qingjie;ZHANG Jianlong;CHEN Yanhua;ZHAO Xuanhao;WAN Yonghua(School of Petroleum Engineering,Changzhou University Changzhou,Jiangsu 213164)
出处 《工业安全与环保》 2020年第2期44-48,共5页 Industrial Safety and Environmental Protection
基金 科技部国际合作司中国波兰双边政府间科技合作项目(2012—35—05) 江苏省高校自然科学重点项目(16KJA170004)。
关键词 城市燃气管网 人工神经网络 预测模型 评价因子 破坏概率 gas pipeline network artificial neural network predictive model evaluation factor failure probability
  • 相关文献

参考文献8

二级参考文献70

共引文献91

同被引文献35

引证文献4

二级引证文献4

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部